NSF Convergence Accelerator Track L: Innovative chemical microsensor development for in situ, real-time monitoring of priority water pollutants to protect water quality

清洁的水对人类生命和自然的健康和福祉是必不可少的。然而，人类活动对水质有深远的影响，往往导致人类和生态系统健康下降，粮食生产减少，整个美国和全球贫困加剧。越来越高的水污染物水平，其中大多数没有得到充分的监测，正在造成一场“隐形水危机”，对低收入社区、部落民族和有色人种社区造成不成比例的影响。该项目旨在开发一个紧凑的、可定制的化学传感系统，与新的微型传感器以及数据管理和分析技术相结合，以准确量化威胁淡水和受管理水系统的人类和生态系统健康的高优先级污染物，并使其可见。这种在工程、环境化学、人工智能和水资源管理方面的专业知识和新兴技术的合作，促进了这些实时、具有成本效益的水监测技术的创新。他们的数据输出将最终提高做出及时、知情的决定和刺激进步行动的能力，以确保社会和地球健康。与不同的利益攸关方(水倡导非营利组织、资源管理者、部落和州政府团体以及环境工程师)的接触将确保这些微型传感器和数据是可访问的和用户友好的，以造福于高风险和服务不足的人群。该项目将利用基于微电子机械系统的技术，通过先进的微制造技术，开发微型、便携式化学传感器，对淡水和受管理的水环境中的多种目标污染物(特别是营养物质和金属)具有非凡的灵敏度(十亿分之一级)和特异性。传感器模块和传感器阵列的远程部署将通过利用嵌入式系统设计和超低功耗系统的先进技术来实现，以延长部署的寿命并实现无线通信以实现实时数据传输。将利用大数据技术确保从这些传感器阵列获得的数据易于获取、准确、组织良好，并可由具有广泛专业知识和需求的最终用户解释，空间人工智能方法将促进水质预测和预报。这一创新的化学传感和数据分析平台将为广泛的应用提供灵敏、选择性、实时、可靠和经济高效的水质监测。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Clean water is essential for the health and wellbeing of human life and of nature. Human activities, however, have far-reaching impacts on water quality, often leading to a decline in human and ecosystem health, reduction in food production, and escalation of poverty throughout the United States and globally. The increasingly high levels of water pollutants, most of which are not adequately monitored, are creating an “invisible water crisis” that disproportionately impacts low-income communities, tribal nations, and communities of color. This project aims to develop a compact, customizable chemical sensing system integrated with new microsensors and data management and analytic technologies to accurately quantify, and make visible, high-priority pollutants that threaten human and ecosystem health of freshwater and managed water systems. This collaboration of expertise and emerging technologies in engineering, environmental chemistry, artificial intelligence, and water resource management enhances the innovation of these real-time, cost-effective water-monitoring technologies. Their data outputs will ultimately improve capabilities for making timely, informed decisions and spurring progressive actions that ensure societal and planetary health. Engagement with diverse stakeholders (water advocacy non-profits, resource managers, tribal and state government groups, and environmental engineers) will ensure that these microsensors and data are accessible and user-friendly to benefit high-risk and underserved populations. Using microelectromechanical systems-based technologies through advanced microfabrication techniques, this project will develop miniaturized, portable chemical sensors with exceptional sensitivity (sub parts-per-billion level) and specificity of multiple target pollutants (specifically, nutrients and metals) in freshwater and managed water environments. Remote deployment of sensor modules and sensor arrays will be enabled by leveraging embedded systems design and ultra-low-power systems advances to extend the lifetime of deployments and enable wireless communications for real-time data transfer. Big Data technologies will be used to ensure that the data obtained from these sensor arrays are readily accessible, accurate, well-organized, and interpretable by end-users with wide-ranging expertise and needs, and spatial artificial intelligence methods will facilitate water quality prediction and forecasting. This innovative chemical sensing and data analytics platform will provide sensitive, selective, real-time, reliable, and cost-effective water quality monitoring for broad applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.